Technical Field
The invention relates to display advertising. More particularly, the invention relates to estimating conversion rate in display advertising from past performance observations along selected data hierarchies.
Description of the Background Art
In the online display advertising world, advertisers try to market their product to many users by embedding their graphical advertisement within the content in publisher Web pages, e.g. the pages of news portals. The advertiser's main goal is to reach the most receptive online audience in the right context, which then engages with their displayed ad and eventually takes a desired action, identified by the type of the campaign, e.g. brand advertising or direct product marketing. The complexity of realizing this goal is so high that advertisers need specialized technology solutions called demand-side platforms (DSP).
DSPs help manage such display advertising campaigns for many different advertisers simultaneously across multiple direct buy markets or ad exchanges, where ad impressions can be acquired through real-time auctions or bidding. In a direct buy market, the impression price is decided in advance according to the business negotiations between publishers and advertisers directly. On the other hand, in a real-time ad exchange, a bid has to be submitted for each impression (submitted via ad calls) by DSPs and the impression is sold to the highest bidder in a public auction. DSPs are the platforms where all the information about users, pages, ads, and campaign constraints come together to make the best decision for advertisers.
Advertisers seek the optimal price to bid for each ad call to maximize their campaign performance. The optimal bid price of an ad impression depends on the value of that impression to a given advertiser. This value is provided to DSPs as a campaign performance parameter in the form of cost-per-click (CPC) or cost-per-action (CPA) goals. If a CPC or CPA goal is set up, then the optimal bid price can be determined from the expected cost-per-impression, which is equal to the click-through-rate (CTR) for this impression multiplied by the CPC goal, or the conversion rate (CVR) multiplied by the CPA goal.
In this scenario, campaign performance directly depends on how well the CTR or CVR can be estimated and the performance optimization can be considered as the problem of accurately estimating CTR or CVR. If these quantities are overestimated, bid prices are always higher than what they should be, the advertiser wastes campaign budget on useless impressions; on the other hand, if these quantities are underestimated, the advertiser misses high-value impressions that may have led to actions and the campaign under delivers.
The CTR and the CVR are directly related to the intention of the user interacting with the ad in a given context and they are fundamentally difficult to model directly and predict. In practice, CVR is even harder to estimate than CTR because conversion events are very rare. Also, the view-through conversions have longer delays in the logging process (sometimes up to a week), which makes the off-line modeling more difficult. Finally, the ad serving system needs to perform in real-time, requiring the CVR or CTR estimation, optimal bid price calculation, and bid submission to exchanges to be completed in a few milliseconds.